Fractional flow reserve determination

ABSTRACT

The present invention relates to a device ( 1 ) for fractional flow reserve determination. The device ( 1 ) comprises a model generator ( 10 ) configured to generate a three-dimensional model (3DM) of a portion of an imaged vascular vessel tree (VVT) surrounding a stenosed vessel segment (SVS), based on a partial segmentation of the imaged vascular vessel tree (VVT). Further, the device comprises an image processor ( 20 ) configured to calculate a blood flow (Q) through the stenosed vessel segment (SVS) based on an analysis of a time-series of X-ray images of the vascular vessel tree (VVT). Still further, the device comprises a fractional-flow-reserve determiner ( 30 ) configured to determine a fractional flow reserve (FFR) based on the three-dimensional model (3DM) and the calculated blood flow.

CROSS-REFERENCE TO PRIOR APPLICATIONS

This application is a continuation of U.S. application Ser. No.15/532,968, filed on Jun. 2, 2017, which is a U.S. National Phaseapplication under 35 U.S.C. § 371 of International Application No.PCT/EP2015/078117, filed on Dec. 1, 2015, which claims the benefit ofEuropean Patent Application No. 14306939.1, filed on Dec. 2, 2014. Theseapplications are hereby incorporated by reference herein.

FIELD OF THE INVENTION

The present invention relates to the field of coronary angiography. Inparticular, the present invention relates to a device and a method forfractional flow reserve determination.

BACKGROUND OF THE INVENTION

Coronary angiography allows for excellent visualization of coronaryarteries. However, assessment of functional stenosis severity islimited. Fractional flow reserve, FFR, is a reliable measure for gradingstenosis. Based on the aortic pressure P_(a) and the pressure P_(d)distal total stenosis, FFR is defined as: FFR=P_(d)/P_(a).

Recently, the so-called virtual FFR method is receiving increasinginterest for replacing the invasive pressure measurements bycomputational fluid dynamics simulation. This method is based on ageometric model of the coronary tree, which can be obtained either fromcomputer-aided tomography angiography or from X-ray angiography images.

To evaluate the hemodynamic severity of coronary stenosis is a criticaltask in planning of cardiac interventions. Traditionally, the localreduction of the vessel diameter at the stenosis is assessed visually oncardiac images for this purpose.

U.S. Pat. No. 8,157,742 B2 describes a system for planning treatment fora patient. The system may include at least one computer systemconfigured to receive patient-specific data regarding a geometry of ananatomical structure of the patient, create a three-dimensional modelrepresenting at least a portion of the anatomical structure of thepatient based on the patient-specific data, and determine a firstfractional flow reserve within the anatomical structure of the patientbased on the three-dimensional model and a physics-based model relatingto the anatomical structure of the patient.

WO 2014/072861 A2 describes methods and systems for fractional flowreserve calculations, wherein classifying of an unknown fractional flowreserve metric for a cardiac vessel with a stenosis as one of aplurality of different pre-defined classes based on extracted featuresand a learning model is performed.

SUMMARY OF THE INVENTION

There may be a need to improve devices and methods for fractional flowreserve determination.

This is met by the subject-matter of the independent claims. Furtherexemplary embodiments are evident from the dependent claims and thefollowing description.

A first aspect of the present invention relates to a device forfractional flow reserve determination. The device comprises a modelgenerator, which is configured to generate a three-dimensional model ofa portion of an imaged vascular vessel tree surrounding a stenosedvessel segment, based on a partial segmentation of the imaged vascularvessel tree. Further, the device comprises an image processor, which isconfigured to calculate a blood flow through the stenosed vessel segmentbased on an analysis of a time-series of X-ray images of the vascularvessel tree. Still further, the device comprises afractional-flow-reserve determiner, which is configured to determine afractional flow reserve based on the three-dimensional model and thecalculated blood flow.

The imaged vascular vessel tree may be modeled by creating athree-dimensional model representing at least a portion of the vascularvessel tree of a patient.

The present invention is based on a combination of the fractional flowreserve simulation with flow velocity measurements from angiographicimages. For example, the flow velocity measurements may be based on ananalysis, for example on an image processing analysis such as an imagebrightness analysis or an intensity analysis or contrast analysis.

The present invention advantageously improves the reliability of theboundary conditions of the simulated fractional flow reserve, since anaccurate determination of the fractional flow reserve is provided.Further, the present invention advantageously reduces the geometricmodeling requirements, since a blood flow through the stenosed vesselsegment can be calculated with improved precision.

The present invention advantageously provides a combination offractional flow reserve simulations with flow velocity measurements froma series of X-ray images, in particular angiographic images. A region ofinterest is marked in a first angiographic image and tracked over timein the subsequent images of the series following an injection of acontrast agent.

For example, by integrating the calibrated image intensities over theregion of interest, the volumetric flow Q can be calculated as the slopeof the time intensity curve at the time of arrival of the contrastbolus. Further, the aortic pressure is measured using known techniquesas an inlet boundary condition.

For example, the present invention advantageously uses deriving theblood flow through the stenosis from a series of X-ray images andmeasuring the aortic pressure in order to calculate a correctedfractional flow reserve.

The present invention advantageously allows calculating, for example,the distal pressure at the stenosis from the determined FFR and ameasurement of the aortic pressure.

According to a further, second aspect of the present invention, amedical imaging system is provided comprising a display device and adevice according to the first aspect of the present invention oraccording to any implementation form of the first aspect of the presentinvention. The display device is configured to display the determinedfractional flow reserve.

According to a further, third aspect of the present invention, a methodfor fractional flow reserve determination is provided, the methodcomprising the steps of:

a) generating a three-dimensional model of an imaged vascular vesseltree based on a partial segmentation of an imaged vascular vessel treesurrounding a stenosed vessel segment by a model generator;

b) calculating a blood flow through the stenosed vessel segment based onan analysis of a time-series of X-ray images by an image processor; and

c) determining a fractional flow reserve based on the three-dimensionalmodel of the imaged vascular vessel tree and the calculated blood flowby a fractional-flow-reserve determiner.

According to an exemplary embodiment of the present invention, the imageprocessor is configured to conduct the analysis of the time-series ofX-ray images within a period of up to 12 s, preferably of up to 5 s,most preferably of up to 1 s. This advantageously provides a temporalevaluation of the blood flow through the stenosed vessel.

According to an exemplary embodiment of the present invention, thedevice further comprises a controllable injector configured to provide apredefined flow profile of a contrast agent injected into the vascularvessel tree. This advantageously provides a reliable and normalizedblood flow detection and analysis.

According to an exemplary embodiment of the present invention, the imageprocessor is configured to perform a brightness calibration prior to theanalysis of the time-series of X-ray images. This advantageouslyimproves the accuracy of the blood flow detection and measurement.

According to an exemplary embodiment of the present invention, the imageprocessor is configured to perform the brightness calibration by top-hatfiltering or by image filtering or by bone removal or by digitalsubtraction of a reference image in at least one image of thetime-series of X-ray images or in an image recorded prior to therecording of the time-series of X-ray images. The image filtering mayrefer to a preprocessing or filtering technique which improves thebrightness analysis. This could also be dual energy angiography orangiography using a spectral detector which enables accurate iodinequantification.

In an example, the image processor is configured to calculate the bloodflow using calibrated intensities over a region of interest includingthe stenosed vessel segment. This advantageously improves the accuracyof the blood flow detection and measurement. According to an exemplaryembodiment of the present invention, the image processor is configuredto calculate the blood flow using a slope of a plot of the calibratedintensities as a function of integration time. This advantageously alsoimproves the accuracy of the blood flow detection and measurement.

According to an exemplary embodiment of the present invention, thefractional-flow-reserve determiner is configured to calculate thefractional flow reserve using at least one boundary condition on aninlet and/or an outlet of the imaged vascular vessel tree.Advantageously, this improves the accuracy of the blood flow detectionand measurement, too.

According to an exemplary embodiment of the present invention, thefractional-flow-reserve determiner is configured to use as the at leastone boundary condition a pressure flow or flow constraint or a lumpedelement model composed of a resistor, a non-linear resistor or acapacitor. Improving the accuracy of the blood flow detection andmeasurement is advantageously also achieved.

The term “lumped element model” as used by the present invention refersto a parameter model that simplifies the description of the behavior ofspatially distributed physical systems into a topology consisting ofdiscrete entities that approximate the behavior of the distributedsystem under certain assumptions.

According to an exemplary embodiment of the present invention, thefractional-flow-reserve determiner is configured to adjust the at leastone boundary condition to a determined diameter of a vessel of theimaged vascular vessel tree. This advantageously improves the accuracyof the blood flow detection and measurement.

According to an exemplary embodiment of the present invention, thefractional-flow-reserve determiner is configured to calculate a distalpressure of the stenosed vessel segment using a three-dimensional fluiddynamics simulation or a lumped components model, wherein a resistanceof the stenosed vessel segment is approximated from a cross-sectionalarea of the stenosed vessel segment. This advantageously provides areliable and normalized blood flow detection and analysis.

According to an exemplary embodiment of the present invention, the modelgenerator is configured to generate the three-dimensional model of theportion of the imaged vascular vessel tree based on a portion of thevascular vessel tree distal to the stenosed vessel segment.

These and other aspects of the present invention will become apparentfrom and be elucidated with reference to the embodiments describedhereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete appreciation of the present invention and the attendantadvantages thereof will be more clearly understood with reference to thefollowing schematic drawings, which are not to scale, wherein:

FIG. 1 shows a schematic diagram of region of interest on an imagevascular vessel tree for explaining the present invention;

FIG. 2 shows a schematic diagram of an intensity as a function of timeplot for explaining the present invention;

FIG. 3 shows a schematic diagram of a simple geometric model of astenosed vessel segment for explaining the present invention;

FIG. 4 shows a schematic diagram of a coronary vessel tree with typicalboundary conditions for explaining the present invention;

FIG. 5 shows a schematic diagram of a complete segmentation of thecoronary vessels and the proposed reduced segmentation for explainingthe present invention;

FIG. 6 shows a schematic diagram of a flowchart diagram for explainingthe present invention;

FIG. 7 shows a schematic diagram of a device for fractional flow reservedetermination according to an exemplary embodiment of the presentinvention;

FIG. 8 shows a schematic diagram of a medical imaging device accordingto an exemplary embodiment of the present invention; and

FIG. 9 shows a schematic diagram of a flowchart diagram of a method forfractional flow reserve determination according to an exemplaryembodiment of the present invention.

DETAILED DESCRIPTION OF EMBODIMENTS

The illustration in the drawings is purely schematic and does not intendto provide scaling relations or size information. In different drawingsor figures, similar or identical elements are provided with the samereference numerals. Generally, identical parts, units, entities or stepsare provided with the same reference symbols in the description.

FIG. 1 shows a schematic diagram of a region of interest on an imagevascular vessel tree for explaining the present invention.

In FIG. 1, an imaged vascular vessel tree VVT is shown and a partialsegmentation of the image vascular vessel tree VVT is performed around astenosed vessel segment SVS of interest.

According to an exemplary embodiment of the present invention, thegeometric model of the coronary tree can be obtained by segmentation ofcardiac computed tomography, CT, image volumes or from a few preferablytwo orthogonal X-ray angiography projections.

A quantitative measurement of the blood flow in the stenosed segment maybe performed. For example, a densitometric approach may be suited toestimate the flow from a short time-series of X-ray angiography images.

A power injector, or a controllable injector, e.g. an injector module,can be used to minimize the dilution of the contrast agent with blood.For quantitative measurement of the contrast agent inflow, the image maybe calibrated properly. To this end, scatter and background structuresmay be removed (e.g. by top-hat filtering, bone removal or by digitalsubtraction of a reference image) and the imaged intensity may becalibrated (e.g. using a phantom with known attenuation or usinginformation of the three-dimensional vessel geometry). A region ofinterest, ROI, may be marked, as illustrated later on in FIG. 3, andtracked over time.

FIG. 2 shows a schematic diagram of an intensity as a function of timeplot for explaining the present invention. According to an exemplaryembodiment of the present invention, when integrating the calibratedintensities over the ROI, the volumetric blood flow Q can be calculatedas the slope of the curve at bolus arrival time as shown in FIG. 2.Contrast transit-time or arrival-time methods for flow quantificationmight also be used, either as an alternative or in combination with thedensitometric approach.

According to an exemplary embodiment of the present invention, as aninlet boundary condition, the aortic pressure can be estimated from armcuff pressure measurements, or can be measured directly using an aorticcatheter, as usually done in interventional cardiology. Using the flowboundary condition, the requirements for geometric modeling aresignificantly relaxed. A typical fractional flow reserve FFR simulationmay be given by a detailed segmentation of the complete coronary tree(including fine distal branches).

FIG. 3 shows a schematic diagram of a simple geometric model of astenosed vessel segment for explaining the present invention. FIG. 3shows a partial segmentation of the image vascular vessel tree VVTaround the stenosed vessel segment SVS.

According to an exemplary embodiment of the present invention, if theblood flow Q through the stenosis and the aortic pressure p_(a) areknown, a model of the stenosed vessel segment alone (as shown in FIG. 3)is sufficient to calculate the distal pressure p_(d). This can beachieved via a full three-dimensional computational fluid dynamicssimulation or by a lumped components approach where the segment'sresistance is approximated from its cross-sectional areas, consideringthe Poiseuille effect (or Poiseuille's Law), the Bernoulli principle andothers. Then, the fractional flow reserve FFR can be calculated as inthe following equation:FFR=P _(d) /P _(a).

FIG. 3 shows a simple geometric model of a stenosed vessel segment. Theinlet and outlet boundary conditions are given by the aortic pressurep_(a) and the flow Q, respectively.

According to an exemplary embodiment of the present invention, theso-called virtual fractional flow reserve (vFFR) method may be used incombination with invasive pressure measurements by computational fluiddynamics (CFD) simulations. CFD simulations may be based on a geometricmodel of the coronary tree, which can be obtained either from CTangiography or from X-ray angiography images. A region of interest, ROI,may be marked and tracked over time.

FIG. 4 shows a schematic diagram of a coronary vessel tree with typicalboundary conditions for explaining the present invention.

For accurate vFFR simulations, the choice of personalized boundaryconditions at the inlets and outlets (as illustrated using FIG. 4) areconsidered. At each inlet and outlet, boundary conditions are assignedfor non-ambiguous definition of all model variables. In general, theseboundary conditions are pressure or flow constraints or lumped elementmodels, composed of resistors, non-linear resistors (varistors) anddynamic elements (such as capacitors). For example, one can impose apressure pin at the inlet (coronary ostium) and a particular resistancegoing to ground to each of the outlets.

The term “varistor” as used by the present invention refers to anelectronic component with a nonlinear current-voltage characteristic,which is therefore also known as a voltage-dependent resistor (VDR).

The error of vFFR simulations depends at least linearly on a correctestimate of the flow value through the stenosis and hence on the correctchoice of boundary conditions. If parts of the coronary tree areexcluded from the segmentation, the flow through the remaining branches(especially through the stenosed segment) and hence the vFFR predictionwould be compromised.

FIG. 5 shows a schematic diagram of a complete segmentation of thecoronary vessels and the proposed reduced segmentation.

According to an exemplary embodiment of the present invention, theboundary conditions (pressures or resistances) at each outlet usuallydepend on the size (e.g. diameter, cross-sectional area) of theout-going vessel relative to the root vessel (e.g. LCA, RCA). Then,scaling laws can be applied to calculate the relative flow or impedanceof each outlet. E.g. in case of a simple outlet resistance, resulting inequation 1:

$R_{out} = {150{\frac{Pa}{m\text{/}s} \cdot \sqrt[3]{\frac{d_{root}}{d_{out}}}}}$

wherein Rout is the outlet resistance, d_(out) is the diameter of theoutlet, droot is the diameter of the root vessel, wherein the expression“Pa” of equation 1 refers to pascal (symbol: Pa) and is the SI derivedunit of pressure, internal pressure, stress, Young's modulus and tensilestrength, defined as one newton per square meter. The expression “m/s”of equation 1 refers to meter per second. Meter per second is an SIderived unit of speed (scalar) and velocity (vector), defined bydistance in meters divided by time in seconds. Calculating the outletresistance requires knowledge of the diameter droot of the root vessel,which is not available with an incomplete segmentation.

According to an exemplary embodiment of the present invention, it isproposed to calculate vFFR with only a partial segmentation of thevascular tree together with an explicit measurement of the diameter ofthe coronary ostium. This measure may be then used in a scaling law forthe boundary conditions, e.g. as droot in equation 1.

The basic principle is illustrated in FIG. 5. Conventionally, a completesegmentation of the coronary vessel tree is preferred to increase theaccuracy of vFFR calculations. A detailed segmentation, however, may betedious and may hamper clinical workflow, especially during cardiacinterventions. As the fractional flow reserve (FFR) value depends mostlyon the stenosis geometry and the flow through the stenosed vesselsegment, a partial segmentation (e.g. of the branches distal to thestenosis) can be sufficient for vFFR calculations if the ostium diameteris used to calculate peripheral resistance, for example by equation 1.

FIG. 5 shows a complete segmentation of the coronary vessel tree (left)and proposed reduced segmentation (right).

According to an exemplary embodiment of the present invention, theostium diameter can be obtained (a) by interactive or (semi-)automatedmeasurement on X-ray images or CT-volumes or (b) approximated by thediameter of coronary catheter, which was chosen by the interventionalradiologist.

In general, it will often be reasonable to exclude the major brancheslocated proximal to a stenosis from the segmentation (as in FIG. 5)without introducing a large error. This is true if the pressure drop Dpfrom the inlet to the cropping point is small, i.e. no stenosis islocated there. This is not very limiting, because if stenoses werelocated there, this branches would be included in the segmentationanyway. The blood flow through the stenosis can then still be estimatedaccurately by flow or impedance boundary conditions with a scaling lawusing the root diameter information.

FIG. 6 shows a schematic diagram of a flowchart diagram for explainingthe present invention.

Initially, a three-dimensional model 3DM of an imaged vascular vesseltree VVT based on a partial segmentation of the imaged vascular vesseltree VVT surrounding a stenosed vessel segment SVS may be calculated.

Then, calculating a blood flow Q through the stenosed vessel segment SVSbased on an analysis of a time-series of X-ray images may be performed.

Subsequently, a fractional flow reserve FFR based on thethree-dimensional model 3DM and the calculated blood flow Q may becalculated.

FIG. 7 shows a schematic diagram of a device 1 for fractional flowreserve determination.

The device 1 for fractional flow reserve determination may comprise amodel generator 10, an image processor 20, and a fractional-flow-reservedeterminer 30.

The model generator 10 may be configured to calculate athree-dimensional model 3DM of an imaged vascular vessel tree VVT on apartial segmentation of an image vascular vessel tree VVT surrounding astenosed vessel segment SVS. The three-dimensional model may be avirtual structure of a vessel structure, a complex branched treestructure, or any other structure as a circuit, wherein the vesselstructure is modeled by a plurality of tubes each of which defined by,for instance parameters like size, length, position, and direction.

The image processor 20 may be configured to calculate a blood flow Qthrough the stenosed vessel segment SVS based on an analysis of atime-series of X-ray images. The analysis may be an image processinganalysis, for instance, a brightness analysis or an image contrastanalysis.

The fractional-flow-reserve determiner 30 may be configured to determinea fractional flow reserve based on the three-dimensional model of theimaged vascular vessel tree VVT and the calculated blood flow Q.

Further, the distance between the location, at which the diameter of theostium was measured, and the part, at which the segmentation of thestenosed vessel segment SVS starts, may be used as an input parameter bythe model generator 10.

FIG. 8 shows a schematic diagram of a medical imaging system 200according to an exemplary embodiment of the present invention.

The medical imaging system 200 may comprise an example of the device 1for fractional flow reserve determination. The medical imaging system200 may be an X-ray guided cardiac medical intervention device, aCT-imaging system or a magnetic resonance (MR) angiography imagingsystem.

Further, the medical imaging system 200 may be used for coronary flowreserve determination.

FIG. 9 shows a schematic diagram of a flowchart of a method forfractional flow reserve determination. The method may comprise thefollowing steps:

As a first step a) of the method, generating S1 a three-dimensionalmodel of an imaged vascular vessel tree VVT based on a partialsegmentation of the imaged vascular vessel tree VVT surrounding astenosed vessel segment SVS by a model generator 10 may be conducted.

As a second step b) of the method, calculating S2 a blood flow Q throughthe stenosed vessel segment SVS based on an analysis of a time-series ofX-ray images by image processor 20 may be conducted.

As a third step c) of the method, determining S3 a fractional flowreserve FFR based on the fractional flow reserve FFR and the calculatedblood flow Q by a fractional-flow-reserve determiner 30 may beconducted.

According to an example, the step of calculating S2 the blood flow Qthrough the stenosed vessel segment SVS comprises calculating the bloodflow Q using calibrated intensities over a region of interest includingthe stenosed vessel segment SVS. In an example, the step of determiningS3 the fractional flow reserve FFR is performed using at least oneboundary condition on an inlet and/or an outlet of the imaged vascularvessel tree VVT.

It has to be noted that embodiments of the present invention aredescribed with reference to different subject-matters. In particular,some embodiments are described with reference to method type claimswhereas other embodiments are described with reference to device typeclaims.

However, a person skilled in the art will gather from the above and theforegoing description that, unless otherwise notified, in addition toany combination of features belonging to one type of the subject-matteralso any combination between features relating to differentsubject-matters is considered to be disclosed with this application.

However, all features can be combined providing synergetic effects thatare more than the simple summation of these features.

While the present invention has been illustrated and described in detailin the drawings and the foregoing description, such illustration anddescription are to be considered illustrative or exemplary and notrestrictive; the present invention is not limited to the disclosedembodiments. Other variations to the disclosed embodiments can beunderstood and effected by those skilled in the art and practicing theclaimed invention, from a study of the drawings, the disclosure, and theappended claims.

In the claims, the word “comprising” does not exclude other elements orsteps, and the indefinite article “a” or “an” does not exclude aplurality. A single processor or controller or other unit may fulfillthe functions of several items recited in the claims. The mere fact thatcertain measures are recited in mutually different dependent claims doesnot indicate that a combination of these measures cannot be used toadvantage. Any reference signs in the claims should not be construed aslimiting the scope.

The invention claimed is:
 1. A device for fractional flow reservedetermination, the device comprising: a processor configured to: receivea time series of X-ray or CT images of an imaged vascular vessel tree,the imaged vascular vessel tree comprising stenosed vessel segment, aproximal vessel segment proximal to the stenosed vessel segment, and adistal vessel segment distal to the stenosed vessel segment, wherein theproximal vessel segment comprises a diameter; generate athree-dimensional model of a portion of the imaged vascular vessel treebased on a segmentation of only the stenosed vessel segment and thedistal vessel segment; calculate a blood flow through the stenosedvessel segment based on an analysis of the time series of X-ray or CTimages of the imaged vascular vessel tree; obtain the diameter of theproximal vessel segment, wherein the proximal vessel segment is excludedfrom the segmentation such that the diameter of the proximal vesselsegment is not obtained based on the segmentation; and determine, usinga plurality of boundary conditions, a fractional flow reserve based onthe three-dimensional model and the calculated blood flow, wherein theplurality of boundary conditions comprises a boundary conditionassociated with the distal vessel segment, wherein the boundarycondition is determined using the diameter of the proximal vesselsegment, wherein the diameter of the proximal vessel segment isapproximated using a diameter of a catheter.
 2. The device of claim 1,wherein the diameter of the proximal vessel segment comprises a coronaryostium diameter.
 3. The device of claim 1, wherein the plurality ofboundary conditions comprises at least one of: a pressure constraint; aflow constraint; or a lumped element model comprising at least one of aresistor, a varistor, or a capacitor.
 4. The device of claim 1, whereinthe processor is further configured to determine at least one boundarycondition of the plurality of boundary conditions using a pressureconstraint derived from an aortic pressure measurement.
 5. The device ofclaim 4, wherein the aortic pressure measurement is an arm cuff pressuremeasurement or an aortic catheter measurement.
 6. The device of claim 1,wherein the three-dimensional model comprises a plurality of tubes eachdefined by at least one of a diameter, a length, a position, or adirection.
 7. The device of claim 1, wherein the processor is furtherconfigured to calculate a distal pressure of the stenosed vessel segmentusing a three-dimensional fluid dynamics simulation or a lumpedcomponents model.
 8. The device of claim 7, wherein a resistance of thestenosed vessel segment is approximated from a cross-sectional area ofthe stenosed vessel segment.
 9. The device of claim 1, wherein theanalysis of the time series of X-ray or CT images has a period of up to1 second, 5 seconds, or 12 seconds.
 10. The device of claim 1, whereinthe analysis of the time series of X-ray or CT images includesdetermining calibrated intensities over a region of interest includingthe stenosed vessel segment.
 11. The device of claim 1, wherein theanalysis of the time series of X-ray or CT images includes usingdensitometry.
 12. The device of claim 1, wherein the processor isconfigured to obtain a measurement of the diameter of the proximalvessel segment on the time series of X-ray or CT images.